Tag: release

Thank you so much for reporting bugs in our Picard 2.0.0beta1 release. We fixed most of the critical bugs that you guys and gals reported. You can find the beta2 release with the fixes here – Picard 2.0.0.beta2

If you have been following our Picard related blogs, you will know that we decided to release a new stable version of Picard before the beginning of the summer.

To help us, advanced users, translators and developers are encouraged to:

Note – If any of you are seasoned Windows/macOS devs and have experience with PyInstaller, we need some help with PICARD-1216 and PICARD-1217. We also need some help with code signing Picard for OSX. Hit us up on #metabrainz on freenode for more information. We will be very grateful for any help that you may offer!

We received so few bug reports on the beta release of the ListenBrainz web site, that we decided to push those changes live and start working on new features. This release is substantially unchanged from our beta release.

The user facing changes that were released include:

Statistic infrastructure: We’ve created an infrastructure for creating graphs of user’s listening behaviour. So far we’ve only got an all-time top-artists graph to illustrate our setup, but soon we will work to create more graphs. Currently graphs will be generated every Monday starting at 0:00 UTC, if you logged in into your LB account during the last 30 days. If you haven’t logged in recently, you can request the calculation of your stats from your profile page.

I have recently released a new MusicBrainz virtual machine. This virtual machine includes all the important bits of MusicBrainz so you can run your own copy! I’d been hoping for feedback if people have encountered any problems with this VM, but I’ve not received any feedback. Here is to hoping that no news is good news!

I’m pleased to announce that we released our first official beta version of ListenBrainz yesterday! As you may know, ListenBrainz is our project to collect, preserve and make available, user listening data similar to what Last.fm has been doing, but with open data.

In 2015 a small group of hackers gathered in London to hack on the first version of ListenBrainz alpha. We threw together a pile of new technologies and released the first version of ListenBrainz at the end of the weekend. In the end, we didn’t really like the new technologies (Cassandra, Kakfa) as both ended giving us a lot of problems that never seemed to end.

In 2016 we embarked on a journey to pick new technologies that we liked better and ended up setting on InfluxDB and RabbitMQ as backbones to our data ingestion pipeline. These tools were a good match for us, since we were already using them in production! Sadly, MetaBrainz’ move to our new hosting provider ended up sucking up any available time we had to devote to the projects, so progress was made in fits and starts.

Earlier this year Param Singh expressed interest to help with the project in hopes of joining us for a Google Summer of Code project. He started submitting a never ending stream of pull requests; slowly the project started moving forwards. Together we brought the codebase up to our current standards and integrated it into the workflow that we use for all of the MetaBrainz projects.

We proceeded to prepare the next version to be released at MetaBrainz’s new hosting facility and started a never ending series of tests. We kept pounding on the data ingestion pipeline, trying to find all of the relevant bugs and ways in which the data flow could get snagged. Finally the number of reported bugs relating to data ingestion dropped to zero and we managed to import 10M listens (a listen is a record of one song being played)!

That was our cue for promoting our pre-beta test to a full beta and unleashing it onto our production servers at our new hosting facility. Today we cleaned up the last bits of the release and we are ready for business!

What does this new release bring for you, the end users? Sadly, only a few new things, since most of the work has gone into building a stable and scalable system. We do have a few new things in this release:

Incremental imports from Last.fm — now you don’t have to do a full import any time you wish to import your latest listens from Last.fm. The importer knows when you last did and import and will work accordingly.

Last.fm compatible submission interface — with some system configuration changes you can submit your listens directly to ListenBrainz from any application with Last.fm support. (more info here)

Last.fm file import — if you have an old skool Last.fm zip file with your listening history backed up, you can now import it.

User data export — you can now download your own listens straight from the site, no waiting required.

Adaptive rate limiting on the API — our server now uses a modern rate limiting system. For details, see our API docs.

The good news is that Param is now working on his Summer of Code project that will add a lot of graphs and other critical elements for making use of this new data set. We hope to release new features on an ongoing basis from here on out.

Most importantly, we want to publicly state that ListenBrainz is now ready for business! We don’t plan to reset the database from here on out — this is the real deal and we plan to safeguard and make this database available as soon as we can. If you have hesitated with sending your listen histories to ListenBrainz in the past, you should now feel free to send your listen information to us! If you are an author of a music player, we ask that you consider adding support for ListenBrainz in your player!

In a follow-up blog post I am going to write about how to start using ListenBrainz now — at the very least use it to back-up your Last.fm listening history!